ameras 0.4.0

Bug fixes

• Fixed a bug causing the inpar check in ameras() to generate an error when it should not.
• Fixed an issue where FMA generated an error instead of returning NULL for generated samples when all individual fits were excluded.
• Fixed an issue where setting keep.data=FALSE and passing data to confint() failed an internal check when effect modifiers were present.
• Fixed an issue where profile likelihood confidence intervals for the ERC method of the proportional hazards family were computed using the non-ERC likelihood, silently ignoring the measurement error correction.
• Removed the isSymmetric check for FMA variance matrices, which caused platform-dependent differences in included realizations due to numerical differences between Cholesky and solve-based computations. The Cholesky-based variance computation now used guarantees exact symmetry without an explicit check.

Improvements

• Reduced memory usage and improved computation speed for large datasets: removed the use of N x N matrices for ERC for the proportional hazards family, and precomputed centered dose matrices for ERC are now stored and reused across likelihood evaluations rather than recomputed at each call.
• confint() no longer recomputes confidence intervals by default if they have already been computed. Use force=TRUE to recompute with different settings. confint() now also prints the computed confidence intervals when called with print=TRUE (default).
• FMA and BMA output now includes a variance-covariance matrix vcov, computed from the model-averaged posterior samples.
• It is now possible to use a dosevars variable defined locally (e.g., within a simulation script) through all_of(dosevars) in the formula passed to ameras().

New methods and accessors

• residuals(): computes Pearson, deviance, and response residuals for all supported families, and Schoenfeld residuals for family="prophaz", supporting both raw and scaled versions following Grambsch and Therneau (1994).
• plot(): diagnostic plots including residuals versus fitted values and normal Q-Q plots. For family="prophaz", Schoenfeld residual plots are produced to assess the proportional hazards assumption.
• vcov(): extracts the variance-covariance matrix of parameter estimates for one or more estimation methods.
• included_realizations(): returns the indices of realizations included in FMA and BMA model averaging.
• Rhat(): returns the Gelman-Rubin convergence diagnostics and effective sample sizes for BMA results.
• summary_table(): extracts the summary table from a summary.amerasfit object as a data frame, for programmatic access to parameter estimates, standard errors, and confidence intervals.

ameras 0.3.0

Breaking changes

• Replaced all occurrences of replicate with realization, including in names of arguments and output. As a result, the argument included.replicates.BMA is now deprecated and will be removed in version 1.0.0. Use included.realizations.BMA instead.

New features

• ecdfplot() now has an argument show.mean (default TRUE) to toggle whether to plot curves for the distribution of the mean doses across realizations and individuals.

Minor improvements and fixes

• Shortened column names CI.lowerbound and CI.upperbound in the summary() output to CI.lower and CI.upper, respectively.

• Substantially increased ERC computation speed for the clogit and prophaz families.

ameras 0.2.0

Breaking changes

• Confidence intervals are no longer computed inside ameras(). The arguments CI, params.profCI, maxit.profCI, and tol.profCI are deprecated and will be removed in version 1.0.0. Use the new confint() method instead. See ?confint.amerasfit for details.

• The direct argument interface to ameras() is deprecated and will be removed in version 1.0.0. The arguments Y, dosevars, doseRRmod, deg, M, X, offset, entry, exit, and setnr are deprecated. Please use the new formula interface instead. See ?ameras for details.

New features

• Implemented a formula interface for ameras(). The dose variable is specified using the special dose() term, which supports tidyselect syntax for selecting dose columns and allows specifying the dose-response model and effect modifiers directly in the formula. See ?ameras for details and examples.

• Added confint.amerasfit() for computing confidence intervals separately from model fitting. See ?confint.amerasfit for details.

• Added function ecdfplot() for exploratory visualization of the dose realizations before model fitting.

General improvements

• Reduced memory usage for large datasets.

  • Removed the use of an N x N matrix for ERC for the Poisson family, improving both memory and computation speed.
  • Removed internal duplication of data for RC and ERC for all families.

• summary.amerasfit() now only includes confidence interval columns after they have been computed via confint(). Before calling confint(), a note is printed directing the user to compute confidence intervals.

• Profile likelihood confidence interval bounds now include p-values in the summary table, making it easier to assess the accuracy of the root-finding algorithm.

• Removed memoization of the profile likelihood function as it was causing issues and likely not providing much benefit.

New arguments

• keep.data added to ameras() (default TRUE). When TRUE, the data are stored on the returned amerasfit object, which is required for profile likelihood confidence interval computation via confint() without re-supplying the data. Set to FALSE to reduce memory usage for large datasets, in which case the data must be supplied to confint() explicitly. See ?ameras and ?confint.amerasfit for details.

ameras 0.1.1

• Initial CRAN submission.